DATA. SMALL WORD. COLOSSAL IMPLICATIONS SPR Consulting

Transcription

1 DATA. SMALL WORD. COLOSSAL IMPLICATIONS SPR Consulting

2 Data, not such a small word after all. Truth is, whether we call it big data or just data, the phenomenon of exponential data growth is upon us. Since ninety percent of the world s data was created in the last two years, something is clearly going on. An explosion of new data sources (social network data, sensor data, images, text messages, etc.) and our increasing capacity to store that data whether structured or unstructured, is the genesis. As a result, methods to measure data volumes have progressed from Gigabytes (a single DVD is thought to hold about 4.7 gigabytes) to Exabytes (5 exabytes is theorized to equal every word ever spoken by humankind.) Indeed things are really moving when the big brains have to make up new words to bring clarity to a topic. Ninety percent of the world s data was created in the last two years. DATA MEASUREMENT CHART DATA MEASUREMENT Bit Byte Kilobyte (KB) Megabyte (MB) Gigabyte (GB) Terabyte (TB) Petabyte (PB) Exabyte (EB) SIZE Single binary digit (1 or 0) 8 Bits 1,024 Bytes 1,024 Kilobytes 1,024 Megabytes 1,024 Gigabytes 1,024 Terabytes 1,024 Petabytes So, what is big data? The term big data encompasses data sets so large, complex and rapidly changing that they are difficult to process using conventional data processing applications. Today, the steep climb in the availability of data is primarily about how people and processes interact with technology. IDC s 3rd Platform; a bold convergence of Cloud, Mobile, Social and Data (the next DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 1

3 big growth engine driving IT spend) fundamentally reflects the multitude of connection points. And there seem to be no boundaries. Users are everywhere, on any device, accessing virtually any data, collaborating and sharing prized tidbits about themselves in the process. The current projections speak to data growth at approximately 40% compounded annually. This unprecedented trajectory will impose significant challenges in storage and processing. The current projections speak to data growth at approximately 40% compounded annually. Data Growth at Approximately 40% Annually 45 Data Volume in Zettabytes Yet there are misconceptions about this bulging trend; such as big data is solely characterized by massive data sets, or used just for unstructured data or only as a replacement for current Business Intelligence systems. None are true. Here s what you can be sure of. Big data technology can cope with a wide variety of structured and unstructured data It can be used for solving prickly issues to truly transform businesses Big data provides an architectural blueprint for storing and analyzing large amounts of diverse data The technology can be complimentary to existing business intelligence investments DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 2

4 Be advised though, the old rules don t apply. The data simply no longer fits within a classical database paradigm. The dynamics of this new data simply can t relate. And traditional tool sets? Well, they don t work. Then there s that growth thing, meaning the data changes lightning fast, by the millisecond. These issues make the promise of exploiting big data a wholly complex endeavor. But if you re inclined to think large volumes of data aren t an asset, think again. Smart organizations who effectively deploy big data technologies can create new models, gain sustained competitive advantage and transform entire industries. To be clear, data is an asset, but not when you re drowning in it. So the mysteries of big data have left many organizations pondering the same questions. Which, in many ways, can be applied to all data analysis scenarios. Smart organizations who effectively deploy big data technologies can create new models, gain sustained competitive advantage and transform entire industries. To be clear, data is an asset, but not when you re drowning in it. How do we make sense of this data? So, making sense of it, that s the goal. And as sometimes happens, the big questions lead to more specific questions which, when answered, can provide direction, guidance and insights. Consider the following: 1 Can you process, store and index all critical data across the organization? Structured, unstructured and other. 2 Do all components of your data management infrastructure work together? Or are there silos with no central access? 3 Do you have insights into customer behavior, sentiment, churn and brand loyalty? How quickly can you gather and act on these insights? 4 Are you adequately addressing industry specific and government mandates for compliance monitoring and data retention? DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 3

5 5 Do you have big data expertise in house to handle explosive data growth and the demand to deliver meaningful insights to the business? 6 Can you draw connected actionable intelligence from the combination of: Traditional transactional data New network of things - machine data Do you have big data expertise in house to handle explosive data growth and the demand to deliver meaningful insights to the business? Unstructured data / social media Disparate knowledge worker documents and records Because big data and business intelligence technologies provide solutions to every question above, your answers will directly expose whether you should launch a plan to gain more realized value from your data. What big problems do we have that this data could help solve, and what business opportunities does big data offer your organization? 30% Insights to drive operational efficiency 23% Insights to drive product/service optimization 23% Ability to attract, grow, and retain customers 13% 11% Insights to drive channel efficiency Fraud detection and risk management Results based on survey of 1,000 CIOs DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 4

6 The place to start is to have an unbiased critical look at your business. What are the specific outcomes you want to achieve? Attracting new customers and retaining the ones you have might top the list. Or the ability to better manage risk and avert fraud may be a priority. Uncovering corroborating triggers can also lead you to areas of opportunity, as they typically confirm the need to focus more deeply on a specific area. Many organizations have found substantive value in considering the subjects listed below. a Apply IT Operations Analytics Since cloud and virtualization are super prevalent, IT departments can no longer claim sole control over all the elements they employ to support the business. Operational analytics can go a long way to predict problems and help identify issues before they create disruption. The outcome of these insights are demonstrated to enhance and improve operational efficiencies. Uncovering corroborating triggers can also lead you to areas of opportunity, as they typically confirm the need to focus more deeply on a specific area. Triggers: A recurring or sporadic system or network issue that needs to be pinpointed The need to achieve a single, comprehensive view of fragmented IT operations The necessity to attain ROI improvement by streamlining IT operations b Extend Product/Service Efficiencies Getting the right products or services to customers on time and with a high level of excellence is an absolute must. If the process of getting your offerings from development to fulfillment has verifiable flaws, effective methods to mitigate those must be defined and applied. The pace of business today will not support sustained growth if these types of issues aren t uncovered and successfully addressed. DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 5

7 Triggers: Missing product delivery timeframes with consistency Regular pushbacks of service delivery milestones Clients negotiating lower prices due to service problems c Invoice payments being held up because of quality or delivery issues Understand Customer Sentiment This is a complex problem in a multi-channel world. The reality of virtually constant engagement between you and your customers, and your customers with each other, is certain to present significant challenges. Effectively comprehending sentiment can help you determine the kind of experiences your customers have on your properties, as well as deliver knowledge around what offers will generate more revenue. Because the internet is a 24/7 focus group, splattered with unfiltered opinions and perceptions; you ll want to know who s saying what to whom. The extent of this data s usefulness is unfathomable. Triggers: Because the internet is a 24/7 focus group, splattered with unfiltered opinions and perceptions; you ll want to know who s saying what to whom. Poor online conversion rates Difficulty attracting new customers and diminishing retention levels Shrinking revenue what are my customers thinking? Sudden shifts in customer opinion DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 6

8 d Tighten Risk Management and Fraud Detection Numerous surveys establish that modern CIOs fear one thing above all else, the threat of data theft and the corresponding security breach. The expanding volumes of critical data housed and maintained by organizations, as well as the varied and growing access points makes this a legitimate worry. Similarly, CIOs are increasing their focus on risk management and fraud detection with a clear eye on identifying, assessing, and prioritizing risks. Big Data and Business Intelligence tools can bring solid value towards identifying and circumventing a variety of potential dangers. Triggers: Numerous surveys establish that modern CIOs fear one thing above all else, the threat of data theft and the corresponding security breach. A high incidence of black swan IT projects (having significant cost and schedule overruns) Various proven applications of deficit knowledge resulting in knowledge risks Willful misrepresentation instigating the theft of one or more valuable information assets Large internal/external user sets now need new access to previously insulated apps or data Now that you see more clearly regarding why big data is viable for your organization, and you have some ideas about where you might apply these technologies, let s keep the progress going. DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 7

9 How do we execute effective analytics across the data (structured, unstructured and semi-structured) to realize meaningful results? How? By understanding a few solid steps you should take to move forward. For our purposes, there are seven. 1 Begin collecting data This sounds simple but it s an important first step. If you aren t collecting the data that s being produced, there s no way to reap benefits from the insights. Makes sense, right? At first, you ll want to collect more than is necessary in hopes that much of it will be useful. A potential roadblock is storage costs, in terms of infrastructure and maintenance, as well as people. So take the time to look at existing source systems critically, then determine how (or whether) existing data can be augmented. It s not likely you ll need to keep everything long term, but you won t know until you start. 2 Group data into logical buckets Perform a value analysis on the collected data. Typically, this is the phase of data discovery. Figure out which data sets might provide business value if you analyzed them more carefully. Once the data is organized and prioritized, you can better define where you ll want to apply further analysis. And consider segmenting the amount of data being processed into unique data sets. There are tools available to provide an abstraction framework for performing basic analytics. Figure out which data sets might provide business value if you analyzed them more carefully. 3 Don t throw away your current warehouse and BI platforms Big data processing tools will not replace traditional warehouse and BI platforms in your organization. In fact, these tools are about complementing those environments. Bottom line, you should seek to integrate your big data strategy with your current ecosystem. This will help you gain maximum value from all your assets. DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 8

10 4 Consider using the cloud Forget about trying to figure out how much additional infrastructure you ll need to process and analyze your data. Instead, contemplate the cloud as a first option. Many cloudbased solutions, such as Microsoft Azure, Amazon Web Services and Google offer cost-effective subscription based services for processing big data. 5 Provide self-service Give business users access. They want to benefit from the insights in big data without always turning to IT. So offer something that leans toward self-serve. Stakeholders will need intuitive tools, like drag and drop fields and other easy to act-on options. The goal is to provide them the capabilities to perform custom and iterative analyses. Not only is this powerful for business users but can help IT determine which data is most valuable, contributing to what data is ultimately refined and stored. Stakeholders will need intuitive tools, like drag and drop fields and other easy to act-on options. 6 Establish data governance Historically, data governance is considered to come late in the data management lifecycle. But it s important to institute a business driver policy and sound oversight for big data early on. While executive sponsorship is crucial, business teams must own their big data. Appropriate business cases should provide clear ROI and outline the depth of data analysis required. Key metrics are important to define here, as well. 7 Don t do it alone Understanding how to approach big data can be daunting, especially for data management teams already wall-to-wall with daily data processing requirements. Establishing a dedicated parallel team to work with business stakeholders alongside existing data experts can bring immense value. And keep in mind that a host of new skills will be required. Organizations should consider reaching for external experts to assist in developing a strategy and to take part in the initial implementations. This can accelerate the integration of big data into your org and bring benefits to the table more quickly. DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 9

11 So let s wrap this up. Based on where you are now and the guidance offered here, figuring out your next steps shouldn t be too taxing. And don t save the effort for a future time, if you can avoid it. The sooner you get started plotting a clear direction on how best to capitalize on the data you have (and the data your org is gathering even as we, ahem, speak), the more quickly you ll uncover the many insights that lead to an enviable competitive advantage. And having sustained competitive advantage? Well that s true transformation. About SPR Consulting A trusted partner to businesses for more than 40 years, SPR Consulting builds, integrates, tests and manages technologies that improve enterprise efficiency. With its expert consultants and innovative solutions, SPR improves access to information, company-wide collaboration and helps organizations more effectively connect with their customers. For more information on how SPR powers business with technology, visit Contact SPR Consulting Headquarters Willis Tower 233 South Wacker Dr. Suite 3500 Chicago, Illinois info@spr.com DATA. SMALL WORD. COLOSSAL IMPLICATIONS. 10